Deep Belief Nets in C++ and CUDA C: Volume 2 Autoencoding in the Complex Domain /
Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You'll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers seve...
Κύριος συγγραφέας: | Masters, Timothy (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut) |
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Συγγραφή απο Οργανισμό/Αρχή: | SpringerLink (Online service) |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berkeley, CA :
Apress : Imprint: Apress,
2018.
|
Έκδοση: | 1st ed. 2018. |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Παρόμοια τεκμήρια
-
Deep Belief Nets in C++ and CUDA C: Volume 3 Convolutional Nets /
ανά: Masters, Timothy, κ.ά.
Έκδοση: (2018) -
Deep Belief Nets in C++ and CUDA C: Volume 1 Restricted Boltzmann Machines and Supervised Feedforward Networks /
ανά: Masters, Timothy, κ.ά.
Έκδοση: (2018) -
Data Mining Algorithms in C++ Data Patterns and Algorithms for Modern Applications /
ανά: Masters, Timothy, κ.ά.
Έκδοση: (2018) -
Assessing and Improving Prediction and Classification Theory and Algorithms in C++ /
ανά: Masters, Timothy, κ.ά.
Έκδοση: (2018) -
Python Data Analytics With Pandas, NumPy, and Matplotlib /
ανά: Nelli, Fabio, κ.ά.
Έκδοση: (2018)